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Proceedings Paper

Parallelization of a blind deconvolution algorithm
Author(s): Charles L. Matson; Kathy J. Borelli
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Paper Abstract

Often it is of interest to deblur imagery in order to obtain higher-resolution images. Deblurring requires knowledge of the blurring function - information that is often not available separately from the blurred imagery. Blind deconvolution algorithms overcome this problem by jointly estimating both the high-resolution image and the blurring function from the blurred imagery. Because blind deconvolution algorithms are iterative in nature, they can take minutes to days to deblur an image depending how many frames of data are used for the deblurring and the platforms on which the algorithms are executed. Here we present our progress in parallelizing a blind deconvolution algorithm to increase its execution speed. This progress includes sub-frame parallelization and a code structure that is not specialized to a specific computer hardware architecture.

Paper Details

Date Published: 5 October 2006
PDF: 8 pages
Proc. SPIE 6394, Unmanned/Unattended Sensors and Sensor Networks III, 63940G (5 October 2006); doi: 10.1117/12.680843
Show Author Affiliations
Charles L. Matson, Air Force Research Lab. (United States)
Kathy J. Borelli, KJS Consulting (United States)


Published in SPIE Proceedings Vol. 6394:
Unmanned/Unattended Sensors and Sensor Networks III
Edward M. Carapezza, Editor(s)

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